4 ai ml infrastructure engineer jobs at 3 companies in Vandergrift, PA
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Senior Applied AI Infrastructure Engineer - NREC
Pittsburgh, Pennsylvania, United States
OnsiteFull Time
National Robotics Engineering Center: University robotics research center serving government and industry clients with custom technologies from concept to commercialization.
5+ YOEBachelor's degree or equivalent experience, 5+ years in software engineering, ML infrastructure, DevOps, platform engineering, or developer tools, Python and Linux expertise, and experience with LLMs or AI-assisted workflows.
Agility Robotics: Private U.S. humanoid-robot manufacturer serving warehouses, factories, and distribution centers.
5+ YOERequires 5+ years of software engineering experience, including 2+ years in production ML infrastructure, data platforms, or MLOps; cloud-native, container, IaC, and ML platform experience required.
Hartford or Washington or Tampa or Atlanta or Boston or Charlotte or Trenton or New York or Philadelphia or Pittsburgh
$185k-$235k/yrOnsiteFull Time
World Wide Technology: Global technology solutions provider and digital transformation partner.
10+ YOESenior technical pre-sales architect with 10+ years of experience designing AI/ML infrastructure and platforms, hands-on NVIDIA and cloud experience, strong presentation and whiteboarding skills, and a bachelor’s degree in computer science, engineering, or related field.
NVIDIA DGX, NVIDIA HGX, CUDA, NVIDIA AI Enterprise (NVAIE), NeMo, Omniverse, AWS, Microsoft Azure, GCP, Dell, HPE, Cisco, NetApp, Pure Storage, Vast Data, Advanced Technology Center (ATC), MLOps
AI Solutions Architect - Global Financial Services
Hartford or Washington D.C. or Tampa or Atlanta or Boston or Charlotte or Trenton or New York or Philadelphia or Pittsburgh
$185k-$235k/yrOnsiteFull Time
World Wide Technology: Global technology solutions provider and digital transformation partner.
10+ YOE10+ years in technical pre-sales or solutions architecture; bachelor's in CS/engineering; hands-on AI/ML infrastructure experience; NVIDIA and cloud platform knowledge; strong presentation and whiteboarding skills.
NVIDIA DGX/HGX, CUDA, AI Enterprise, NeMo, Omniverse, AWS, Azure, GCP, Dell, HPE, Cisco, NetApp, Pure Storage, Vast Data, Advanced Technology Center (ATC), NVAIE